UNPKG

@stdlib/strided

Version:
160 lines (120 loc) 4.84 kB
{{alias}}( N, x, sx, y, sy, m, sm, z, sz, fcn ) Applies a binary function to double-precision floating-point strided input arrays according to a strided mask array and assigns results to a double- precision floating-point strided output array. The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use typed array views. Parameters ---------- N: integer Number of indexed elements. x: Float64Array Input array. sx: integer Index increment for `x`. y: Float64Array Input array. sy: integer Index increment for `y`. m: Uint8Array Mask array. sm: integer Index increment for `m`. z: Float64Array Destination array. sz: integer Index increment for `z`. fcn: Function Binary function to apply. Returns ------- z: Float64Array Input array `z`. Examples -------- // Standard usage: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); > var z = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); > var m = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 1, 0 ] ); > {{alias}}( x.length, x, 1, y, 1, m, 1, z, 1, {{alias:@stdlib/math/base/ops/add}} ) <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ] // Using `N` and stride parameters: > z = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); > {{alias}}( 2, x, 2, y, -1, m, 2, z, -1, {{alias:@stdlib/math/base/ops/add}} ) <Float64Array>[ 0.0, 3.0, 0.0, 0.0 ] // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); > var y0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); > var z0 = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); > var m0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 1, 0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); > var z1 = new {{alias:@stdlib/array/float64}}( z0.buffer, z0.BYTES_PER_ELEMENT*2 ); > var m1 = new {{alias:@stdlib/array/uint8}}( m0.buffer, m0.BYTES_PER_ELEMENT*2 ); > {{alias}}( 2, x1, -2, y1, 1, m1, 1, z1, 1, {{alias:@stdlib/math/base/ops/add}} ) <Float64Array>[ 0.0, 6.0 ] > z0 <Float64Array>[ 0.0, 0.0, 0.0, 6.0 ] {{alias}}.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn ) Applies a binary function to double-precision floating-point strided input arrays according to a strided mask array and assigns results to a double- precision floating-point strided output array using alternative indexing semantics. While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. Parameters ---------- N: integer Number of indexed elements. x: Float64Array Input array. sx: integer Index increment for `x`. ox: integer Starting index for `x`. y: Float64Array Input array. sy: integer Index increment for `y`. oy: integer Starting index for `y`. m: Uint8Array Mask array. sm: integer Index increment for `m`. om: integer Starting index for `m`. z: Float64Array Destination array. sz: integer Index increment for `z`. oz: integer Starting index for `z`. fcn: Function Binary function to apply. Returns ------- z: Float64Array Input array `z`. Examples -------- // Standard usage: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); > var z = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); > var m = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 1, 0 ] ); > {{alias}}.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, {{alias:@stdlib/math/base/ops/add}} ) <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ] // Advanced indexing: > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); > y = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); > z = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); > m = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 1, 0 ] ); > {{alias}}.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, {{alias:@stdlib/math/base/ops/add}} ) <Float64Array>[ 0.0, 0.0, 7.0, 0.0 ] See Also --------